Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "161"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 161 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 161, Node N13:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460015 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.171039 32.381761 0.428086 0.013297 0.959108 0.555172 -0.322561 2.539011 0.6019 0.4819 0.3179 nan nan
2460014 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.720247 30.131949 0.232218 -0.284694 0.036919 1.731496 0.135582 1.779202 0.5777 0.4539 0.3246 nan nan
2460013 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.119248 32.681337 0.424878 -0.109792 1.019765 0.484143 -0.157268 1.149490 0.5955 0.4824 0.3227 nan nan
2460012 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.035980 30.913428 0.251700 -0.277414 1.244901 0.635701 0.492082 1.820618 0.5852 0.4753 0.3187 nan nan
2460011 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.045104 32.278314 0.108334 -0.511003 1.350221 1.620070 0.068283 0.598891 0.6070 0.5028 0.3153 nan nan
2460010 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.343970 35.592460 0.051416 -0.125271 0.707570 0.870812 -0.183762 0.944278 0.6183 0.5142 0.3155 nan nan
2460009 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.099260 33.426618 0.297068 -0.019113 0.610687 0.932718 -0.588188 0.485049 0.6195 0.5178 0.3190 nan nan
2460008 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.494606 38.642167 0.226225 -0.157597 -0.086493 0.981128 0.561972 0.548686 0.6623 0.5783 0.2797 nan nan
2460007 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.181081 29.653625 0.331654 0.036767 0.575957 0.479387 -0.069224 1.003892 0.6286 0.5274 0.3050 nan nan
2459999 digital_ok 0.00% 98.91% 99.25% 0.00% - - nan nan nan nan nan nan nan nan 0.2598 0.2254 0.1851 nan nan
2459998 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.387318 26.268092 0.258098 -0.122347 0.579095 0.894666 -0.263376 0.602161 0.6166 0.5082 0.3412 nan nan
2459997 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.534559 28.899944 0.225804 -0.033927 0.423698 0.962703 -0.142858 0.758705 0.6263 0.5167 0.3439 nan nan
2459996 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.285990 31.015432 0.641828 0.110154 0.476167 0.972446 -0.200247 0.126885 0.6391 0.5261 0.3541 nan nan
2459995 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.590011 31.477722 0.150733 -0.267175 0.528496 0.651987 -0.290988 0.104375 0.6221 0.5124 0.3452 nan nan
2459994 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.687936 30.549682 0.208448 -0.123848 0.802851 1.340269 2.244956 3.561609 0.6154 0.5005 0.3442 nan nan
2459993 digital_ok 100.00% 0.00% 0.00% 0.00% - - -1.048097 30.814739 -0.036330 -0.369227 0.243458 1.693242 -0.500090 0.749369 0.5976 0.5046 0.3425 nan nan
2459991 digital_ok 100.00% 0.00% 0.00% 0.00% - - -1.096651 34.791317 0.120592 -0.262542 0.248695 1.277266 -0.345985 0.450808 0.6331 0.5064 0.3509 nan nan
2459990 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.729528 28.668063 0.157982 -0.314807 0.476953 1.536282 -0.476341 0.936739 0.6302 0.5041 0.3460 nan nan
2459989 digital_ok 100.00% 96.81% 97.46% 0.00% - - 200.559429 201.027058 inf inf 2884.303574 2846.344299 4522.274551 4370.875285 0.5348 0.4722 0.2600 nan nan
2459988 digital_ok 100.00% 0.00% 0.00% 0.00% - - -1.004167 34.065336 0.095270 -0.466396 0.214737 2.026794 -0.466583 1.017283 0.6255 0.5110 0.3393 nan nan
2459987 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.658559 28.919864 0.081660 -0.281705 0.257580 0.812559 0.111346 1.358406 0.6346 0.5191 0.3381 nan nan
2459986 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.732925 34.676290 0.113200 -0.418362 0.239047 1.446510 -0.270256 1.084192 0.6524 0.5556 0.2987 nan nan
2459985 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.742360 32.255039 0.104427 -0.342822 -0.089037 0.720099 -0.391900 1.577891 0.6339 0.5173 0.3455 nan nan
2459984 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.725061 31.874529 -0.425881 -0.289909 0.370080 2.200087 1.342922 2.625696 0.6493 0.5399 0.3237 nan nan
2459983 digital_ok 100.00% 0.00% 0.00% 0.00% - - -1.091898 30.412828 0.171010 -0.392760 -0.219363 1.583206 -0.302400 1.061725 0.6627 0.5720 0.2851 nan nan
2459982 digital_ok 100.00% 0.00% 0.00% 0.00% - - -1.115323 23.778531 0.337552 -0.035319 0.566901 0.841085 0.115839 -0.126966 0.7122 0.6110 0.2564 nan nan
2459981 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.992467 27.440913 0.064900 -0.540940 -0.071780 1.715083 -0.490780 0.247909 0.6335 0.5180 0.3423 nan nan
2459980 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.822755 26.017563 -0.034342 -0.549964 -0.167578 1.299413 0.099857 0.196091 0.6768 0.5805 0.2745 nan nan
2459979 digital_ok 100.00% 0.00% 0.00% 0.00% - - -1.033837 28.237109 -0.142308 -0.526050 -0.077863 1.001467 -0.467111 0.184193 0.6261 0.5109 0.3430 nan nan
2459978 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.953289 28.718017 -0.110730 -0.561960 0.158170 1.433372 -0.617589 0.463935 0.6267 0.5113 0.3468 nan nan
2459977 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.845908 29.683410 -0.083015 -0.406062 0.547903 1.659527 0.897616 2.268832 0.5938 0.4794 0.3157 nan nan
2459976 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.958335 28.802548 -0.035429 -0.557145 0.023031 0.995014 -0.600390 0.054336 0.6314 0.5187 0.3388 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 161: 2460015

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 32.381761 32.381761 -0.171039 0.013297 0.428086 0.555172 0.959108 2.539011 -0.322561

Antenna 161: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 30.131949 -0.720247 30.131949 0.232218 -0.284694 0.036919 1.731496 0.135582 1.779202

Antenna 161: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 32.681337 -0.119248 32.681337 0.424878 -0.109792 1.019765 0.484143 -0.157268 1.149490

Antenna 161: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 30.913428 -0.035980 30.913428 0.251700 -0.277414 1.244901 0.635701 0.492082 1.820618

Antenna 161: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 32.278314 -0.045104 32.278314 0.108334 -0.511003 1.350221 1.620070 0.068283 0.598891

Antenna 161: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 35.592460 -0.343970 35.592460 0.051416 -0.125271 0.707570 0.870812 -0.183762 0.944278

Antenna 161: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 33.426618 -0.099260 33.426618 0.297068 -0.019113 0.610687 0.932718 -0.588188 0.485049

Antenna 161: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 38.642167 38.642167 -0.494606 -0.157597 0.226225 0.981128 -0.086493 0.548686 0.561972

Antenna 161: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 29.653625 -0.181081 29.653625 0.331654 0.036767 0.575957 0.479387 -0.069224 1.003892

Antenna 161: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 161: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 26.268092 -0.387318 26.268092 0.258098 -0.122347 0.579095 0.894666 -0.263376 0.602161

Antenna 161: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 28.899944 -0.534559 28.899944 0.225804 -0.033927 0.423698 0.962703 -0.142858 0.758705

Antenna 161: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 31.015432 -0.285990 31.015432 0.641828 0.110154 0.476167 0.972446 -0.200247 0.126885

Antenna 161: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 31.477722 -0.590011 31.477722 0.150733 -0.267175 0.528496 0.651987 -0.290988 0.104375

Antenna 161: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 30.549682 -0.687936 30.549682 0.208448 -0.123848 0.802851 1.340269 2.244956 3.561609

Antenna 161: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 30.814739 -1.048097 30.814739 -0.036330 -0.369227 0.243458 1.693242 -0.500090 0.749369

Antenna 161: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 34.791317 -1.096651 34.791317 0.120592 -0.262542 0.248695 1.277266 -0.345985 0.450808

Antenna 161: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 28.668063 28.668063 -0.729528 -0.314807 0.157982 1.536282 0.476953 0.936739 -0.476341

Antenna 161: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Power inf 201.027058 200.559429 inf inf 2846.344299 2884.303574 4370.875285 4522.274551

Antenna 161: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 34.065336 34.065336 -1.004167 -0.466396 0.095270 2.026794 0.214737 1.017283 -0.466583

Antenna 161: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 28.919864 -0.658559 28.919864 0.081660 -0.281705 0.257580 0.812559 0.111346 1.358406

Antenna 161: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 34.676290 34.676290 -0.732925 -0.418362 0.113200 1.446510 0.239047 1.084192 -0.270256

Antenna 161: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 32.255039 32.255039 -0.742360 -0.342822 0.104427 0.720099 -0.089037 1.577891 -0.391900

Antenna 161: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 31.874529 -0.725061 31.874529 -0.425881 -0.289909 0.370080 2.200087 1.342922 2.625696

Antenna 161: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 30.412828 -1.091898 30.412828 0.171010 -0.392760 -0.219363 1.583206 -0.302400 1.061725

Antenna 161: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 23.778531 -1.115323 23.778531 0.337552 -0.035319 0.566901 0.841085 0.115839 -0.126966

Antenna 161: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 27.440913 27.440913 -0.992467 -0.540940 0.064900 1.715083 -0.071780 0.247909 -0.490780

Antenna 161: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 26.017563 26.017563 -0.822755 -0.549964 -0.034342 1.299413 -0.167578 0.196091 0.099857

Antenna 161: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 28.237109 -1.033837 28.237109 -0.142308 -0.526050 -0.077863 1.001467 -0.467111 0.184193

Antenna 161: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 28.718017 28.718017 -0.953289 -0.561960 -0.110730 1.433372 0.158170 0.463935 -0.617589

Antenna 161: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 29.683410 -0.845908 29.683410 -0.083015 -0.406062 0.547903 1.659527 0.897616 2.268832

Antenna 161: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
161 N13 digital_ok nn Shape 28.802548 28.802548 -0.958335 -0.557145 -0.035429 0.995014 0.023031 0.054336 -0.600390
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